Adaptive decoupling control of a MIMO system based on fuzzy neural networks

According to the control problem of a class of uncertain multiple-input multiple-output (MIMO) nonlinear systems, an adaptive decoupling control approach based on fuzzy neural networks was proposed. Firstly, a sub-channel decoupling control law of MIMO nonlinear systems was designed using decentralized control theory and feedback linearization approach. Secondly, the approximation of the system coupling terms and uncertainty terms were obtained by a fuzzy neural networks observer and compensated into the control law as compensation signal. It was proved that the control law, the observer and the weighted vector adaptive law could guarantee the uniform convergence of the errors of the output variable, the observer variable and the weighted vector finally. Simulations were carried on a typical uncertain MIMO system. The proposed method was compared with a traditional output feedback control method without adding compensation control signal. The simulation results show that the influence caused by coupling among the channels and uncertainty is eliminated by the compensation control and the observer errors can converge. The results validate the effectiveness and stability of the proposed control approach.